The 7 Weak Links in Today’s Software Supply Chains

One important thing is the distinction between SBOM and SCA (Software Composition Analysis). The SBOM is the inventory, or a list of components. SCA evaluates whether any of those components are vulnerable, outdated, or risky. Together, they give organizations the insight needed to make informed decisions, respond more quickly to security issues, and strengthen overall risk management.

The velocity of modern development, coupled with heavy reliance on third-party and open-source code, has introduced severe vulnerabilities. Threat actors are exploiting seven primary weak links:

When developers prioritize speed, they often use large open-source libraries without a full code review. A single component may introduce additional transitive dependencies. If you only monitor the top level, you can miss malicious code injected into those hidden transitive dependencies.

This pattern is something we continue to see across open-source ecosystems. One compromised package can cascade through dependency chains and reach millions of downloads before anyone notices. A recent npm supply chain attack involving crypto-malware highlights exactly how this happens in practice.

Best practices:

• Scan all open-source packages and their full dependency chains to identify vulnerabilities, outdated components, or hidden malware before they reach your codebase.
• Continuously monitor dependencies over time, since safe components can become risky as new CVEs or malicious updates appear.
• Use trusted registries and verify package integrity to ensure the packages you download haven’t been tampered with.
• Apply policies that flag or block risky licenses so incompatible or viral license terms don’t slip into your builds.
• Delay using newly published packages until they've been vetted, reducing the chance of pulling unreviewed or malicious releases into your environment.

Licensing issues now affect engineering as much as legal. Viral licenses, such as the GPL, can force your resulting application to be published under the same license, potentially causing your company to lose its own Intellectual Property (IP). Continuous monitoring is necessary because license terms can change, even for older, previously compliant versions.

Best practices:

• Use an automated license detection tool to flag high-risk or incompatible licenses early in development. A deeper explanation of why this matters is outlined here: The Crucial Role of License Detection in Open Source Security.
• Continuously track license changes to catch shifts that may affect compliance or IP exposure.
• Block or review components with restrictive or viral licenses before they enter the codebase.
• Maintain a clear inventory of all licenses in use to simplify audits and risk assessments.

While regulations mandate sharing SBOMs, a high-level list is insufficient. Detailed data points, including the author, contributors, release frequency, and maintenance status, are needed for effective mitigation and prevention.

Best practices:

• Enhance SBOM reports by rescanning components to enrich them with updated license data, vulnerability status, and other critical metadata. A detailed example of how to do this is outlined here under CycloneDX SBOM Report Validation and Enrichment.
• Validate and enrich SBOMs using automated tools to ensure the information is complete, accurate, and actionable.
• Require vendors to provide full SBOM depth, including transitive dependencies and all relevant metadata.
• Continuously update and monitor SBOM inventories as components evolve or new vulnerabilities emerge.

Every vendor you rely on becomes part of your supply chain. If they ship outdated or compromised components, you inherit that risk. Complete SBOMs, including transitive dependencies, make it possible to understand your exposure quickly instead of chasing vendors during an incident. A recent post on Managing Dependency Vulnerabilities in Your Software Supply Chain explores how teams can strengthen this part of the process.

Due to the rapid adoption of AI, teams are often bypassing normal restrictions, making this a major attack vector. Attackers inject malicious code into machine learning models, PICO files, or open-source libraries. Typosquatting is common in environments like Pytorch, where users might pull the wrong library, which can deliver malware and lead to full remote code execution on an engineer's machine.

Scanning containers must evolve beyond focusing only on vulnerabilities. Modern security must also scan for malware, crypto miners, and fast-acting threats published in publicly available container images. A recent analysis of the NVIDIA Container Toolkit CVE-2024-0132 shows how easily these issues can be overlooked.